Searching journal content for articles similar to Biase et al. 24 (11): 1787.

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  1. Method: Quantifying pathological progression from single-cell transcriptomic data with scPSS
    • Samin Rahman Khan,
    • M Saifur Rahman,
    • M. Sohel Rahman,
    • and Md Abul Hassan Samee
    Genome Res. February 2026 36: 375-386; Published in Advance January 14, 2026, doi:10.1101/gr.280411.125
    ...of Computer Science and Engineering, Bangladesh University of Engineering and Technology, Dhaka-1000, Bangladesh; 4Department of Integrative Physiology, Baylor College of Medicine, Houston, Texas 77030, USA Corresponding authors: msrahman@cse.buet.ac.bd, samee@bcm.eduAbstractThe surge in single-cell data sets...
  2. Method: Batch correction methods used in single-cell RNA sequencing analyses are often poorly calibrated
    • Sindri Emmanúel Antonsson and
    • Páll Melsted
    Genome Res. August 2025 35: 1832-1841; Published in Advance July 7, 2025, doi:10.1101/gr.279886.124
    ...Sindri Emmanúel Antonsson and Páll Melsted Faculty of Industrial Engineering, Mechanical Engineering, and Computer Science, University of Iceland, 102 Reykjavík, Iceland Corresponding author: pmelsted@hi.isAbstractAs the number of experiments that employ single-cell RNA sequencing (scRNA-seq) grows...
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  3. Research: Long-read single-cell RNA sequencing enables the study of cancer subclone-specific genotypes and phenotypes in chronic lymphocytic leukemia
    • Gage S. Black,
    • Xiaomeng Huang,
    • Yi Qiao,
    • Philip Moos,
    • Deepa Sampath,
    • Deborah M. Stephens,
    • Jennifer A. Woyach,
    • and Gabor T. Marth
    Genome Res. April 2025 35: 686-697; Published in Advance February 18, 2025, doi:10.1101/gr.279049.124
    ...-mutated subclones exhibit distinct transcriptomic behavior when compared to other cancer subclones. To achieve these goals, we use scBayes, which integrates bulk DNA sequencing and single-cell RNA sequencing (scRNA-seq) data to genotype individual cells for subclone-defining mutations. Although the most common...
  4. Method: Polyomino reconstructs spatial transcriptomic profiles with single-cell resolution via a region-allocation method
    • Quanyou Cai,
    • Lihui Lin,
    • Xin Liu,
    • and Jiekai Chen
    Genome Res. November 2025 35: 2513-2526; Published in Advance October 22, 2025, doi:10.1101/gr.280532.125
    ...allocating with the algorithm.Mapping single-cell data to in situ sequencing spatial dataFor STARMAP data (Wang et al. 2018), we performed spatial mapping of processed Smart-seq2 snRNA-seq data (Tasic et al. 2018), consisting of 14,249 cells and 34,041 genes, onto 1523 spatial cells. Because STARMAP detected...
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  5. Method: De novo detection of somatic variants in high-quality long-read single-cell RNA sequencing data
    • Arthur Dondi,
    • Nico Borgsmüller,
    • Pedro F. Ferreira,
    • Brian J. Haas,
    • Francis Jacob,
    • Viola Heinzelmann-Schwarz,
    • Tumor Profiler Consortium,
    • and Niko Beerenwinkel
    Genome Res. April 2025 35: 900-913; Published in Advance March 19, 2025, doi:10.1101/gr.279281.124
    ....beerenwinkel@bsse.ethz.chAbstractIn cancer, genetic and transcriptomic variations generate clonal heterogeneity, leading to treatment resistance. Long-read single-cell RNA sequencing (LR scRNA-seq) has the potential to detect genetic and transcriptomic variations simultaneously. Here, we present LongSom, a computational workflow leveraging...
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  6. Method: Recovering gene regulatory networks in single-cell multi-omics data with PRISM-GRN
    • Wenhao Zhang,
    • Lan Cao,
    • Xiaoxuan Gu,
    • Yongyu Long,
    • and Ying Wang
    Genome Res. January 2026 36: 142-158; Published in Advance October 9, 2025, doi:10.1101/gr.280757.125
    ...and target genes (Gao et al. 2023).Single-cell RNA sequencing (scRNA-seq) enables gene expression profiling at the individual cell level, revealing cellular heterogeneity with single-cell resolution and significantly enhancing the understanding of cell type–specific gene regulation (Chen and Liu 2022; Kartha...
  7. Method: Label-free selection of marker genes in single-cell and spatial transcriptomics with geneCover
    • An Wang,
    • Stephanie Hicks,
    • Donald Geman,
    • and Laurent Younes
    Genome Res. December 2025 35: 2744-2755; Published in Advance November 12, 2025, doi:10.1101/gr.280539.125
    ...for Imaging Science, Johns Hopkins University, Baltimore, Maryland 21218, USA Corresponding author: awang87@jhu.eduAbstractThe selection of marker gene panels is critical for capturing the cellular and spatial heterogeneity in the expanding atlases of single-cell RNA sequencing (scRNA-seq) and spatial...
  8. Review: Understanding isoform expression by pairing long-read sequencing with single-cell and spatial transcriptomics
    • Natan Belchikov,
    • Justine Hsu,
    • Xiang Jennie Li,
    • Julien Jarroux,
    • Wen Hu,
    • Anoushka Joglekar,
    • and Hagen U. Tilgner
    Genome Res. November 2024 34: 1735-1746; doi:10.1101/gr.279640.124
    ...gene. Distinct isoforms can play important biological roles, including by changing the sequences or expression levels of protein products. The first single-cell approaches to RNA sequencing—and later, spatial approaches—which are now widely used for the identification of differentially expressed genes...
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  9. Research: Integrating short-read and long-read single-cell RNA sequencing for comprehensive transcriptome profiling in mouse retina
    • Meng Wang,
    • Yumei Li,
    • Jun Wang,
    • Soo Hwan Oh,
    • Yexuan Cao,
    • and Rui Chen
    Genome Res. April 2025 35: 740-754; Published in Advance March 6, 2025, doi:10.1101/gr.279167.124
    ...a systematic comparison between single-cell long-read and conventional short-read RNA sequencing techniques. The transcriptome of approximately 30,000 mouse retina cells was profiled using 1.54 billion Illumina short reads and 1.40 billion Oxford Nanopore Technologies long reads. Consequently, we identify 44...
  10. Method: Single-cell Rapid Capture Hybridization sequencing reliably detects isoform usage and coding mutations in targeted genes
    • Hongke Peng,
    • Jafar S. Jabbari,
    • Luyi Tian,
    • Changqing Wang,
    • Yupei You,
    • Chong Chyn Chua,
    • Natasha S. Anstee,
    • Noorul Amin,
    • Andrew H. Wei,
    • Nadia M. Davidson,
    • Andrew W. Roberts,
    • David C.S. Huang,
    • Matthew E. Ritchie,
    • and Rachel Thijssen
    Genome Res. April 2025 35: 942-955; Published in Advance January 10, 2025, doi:10.1101/gr.279322.124
    ...-read single-cell RNA sequencing (scRNA-seq) data reveals significant gene expression differences in SF3B1-mutated CLL cells, although it does not impact the sensitivity of the anticancer drug venetoclax. scRaCH-seq's capability to study long-read transcripts of multiple genes makes it a powerful tool...
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